Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm is utilized for snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other methods, potentially allowing for online reconstruction. The algorithm’s regularization term is represented using a neural network with 3D convolutional layers to exploit the spatio-spectral correlations that exist in laser wavefronts. Compressed sensing is not typically applied to modulated signals, but we demonstrate its success here. Furthermore, we train a neural network to predict the wavefronts from a lateral shearing interferogram in terms of Zernike polynomials, which again increases the speed of our technique without sacrificing fidelity. This method is supported with simulation-based results. While applied to the example of lateral shearing interferometry, the methods presented here are generally applicable to a wide range of signals, including Shack–Hartmann-type sensors. The results may be of interest beyond the context of laser wavefront characterization, including within quantitative phase imaging.

Attosecond soft X-ray pulses are of great importance for the study of ultrafast electronic phenomena. In this paper, a feasible method is proposed to generate isolated fully coherent attosecond soft X-ray free electron laser via optical frequency beating. Two optical lasers with the opposite frequency chirps are used to induce a gradient frequency energy modulation, which helps to generate a gradually varied spacing electron pulse train. Subsequently, the undulator sections with electron beam delay lines are used to amplify the target ultra-short radiation. Numerical start-to-end simulations have been performed and the results demonstrate that an isolated soft X-ray pulse with the peak power of 330 GW and pulse duration of 620 as can be achieved by the proposed technique.

The optimum parameters for the generation of synchrotron radiation in ultraintense laser pulse interactions with planar foils are investigated with the application of Bayesian optimization, via Gaussian process regression, to 2D particle-in-cell simulations. Individual properties of the synchrotron emission, such as the yield, are maximized, and simultaneous mitigation of bremsstrahlung emission is achieved with multi-variate objective functions. The angle-of-incidence of the laser pulse onto the target is shown to strongly influence the synchrotron yield and angular profile, with oblique incidence producing the optimal results. This is further explored in 3D simulations, in which additional control of the spatial profile of synchrotron emission is demonstrated by varying the polarization of the laser light. The results demonstrate the utility of applying a machine learning-based optimization approach and provide new insights into the physics of radiation generation in laser–foil interactions, which will inform the design of experiments in the quantum electrodynamics (QED)-plasma regime.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

A single-shot measurement of electron emittance was experimentally accomplished using a focused transfer line with a dipole. The betatron phase of electrons based on laser wakefield acceleration (LWFA) is energy dependent owing to the coupling of the longitudinal acceleration field and the transverse focusing (defocusing) field in the bubble. The phase space presents slice information after phase compensation relative to the center energy. Fitting the transverse size of the electron beam at different energy slices in the energy spectrum measured 0.27 mm mrad in the experiment. The diagnosis of slice emittance facilitates local electron quality manipulation, which is important for the development of LWFA-based free electron lasers. The quasi-3D particle-in-cell simulations matched the experimental results and analysis well.

As a typical plasma-based optical element that can sustain ultra-high light intensity, plasma density gratings driven by intense laser pulses have been extensively studied for wide applications. Here, we show that the plasma density grating driven by two intersecting driver laser pulses is not only nonuniform in space but also varies over time. Consequently, the probe laser pulse that passes through such a dynamic plasma density grating will be depolarized, that is, its polarization becomes spatially and temporally variable. More importantly, the laser depolarization may spontaneously take place for crossed laser beams if their polarization angles are arranged properly. The laser depolarization by a dynamic plasma density grating may find application in mitigating parametric instabilities in laser-driven inertial confinement fusion.

The acoustic pulse emitted from the Bragg peak of a laser-accelerated proton bunch focused into water has recently enabled the reconstruction of the bunch energy distribution. By adding three ultrasonic transducers and implementing a fast data analysis of the filtered raw signals, I-BEAT (Ion-Bunch Energy Acoustic Tracing) 3D now provides the mean bunch energy and absolute lateral bunch position in real-time and for individual bunches. Relative changes in energy spread and lateral bunch size can also be monitored. Our experiments at DRACO with proton bunch energies between 10 and 30 MeV reveal sub-MeV and sub-mm resolution. In addition to this 3D bunch information, the signal strength correlates also with the absolute bunch particle number.

The laser-damage performance of optics is known to be negatively affected by microscale particle contamination induced by the operational environment. This work investigates the properties of particles accumulating in various locations near critical optics inside the OMEGA EP grating compressor chamber during quarterly operational periods over a 2-year duration. The particles found were characterized using optical microscopy, scanning electron microscopy and energy dispersive X-ray spectroscopy. The analysis indicates significant concentrations of micrometer- to nanometer-scale particles inside the vacuum chamber, with higher values observed near the port leading to the OMEGA EP target chamber. The distribution of the chemical composition of these particles varies between collection periods. Although understanding of the mechanisms of particle generation and transport remains uncertain, the hypothesis is that this particle load represents a risk for contaminating the surfaces of high-value optics located inside the chamber, including the compression gratings and deformable mirrors, and therefore affecting their laser-damage resistance and overall operational lifetime.

On behalf of all at High Power Laser Science and Engineering we would like to congratulate the team at Lawrence Livermore National Laboratory (LLNL) on demonstrating fusion ignition at the National Ignition Facility. This major scientific achievement was realized on the 5 December 2022 at the LLNL and announced at a press briefing on the 13 December 2022 by the United States Department of Energy’s National Nuclear Security Administration. This was a historic milestone and the culmination of decades of effort.

Pulse shaping is a powerful tool for mitigating implosion instabilities in direct-drive inertial confinement fusion (ICF). However, the high-dimensional and nonlinear nature of implosions makes the pulse optimization quite challenging. In this research, we develop a machine-learning pulse shape designer to achieve high compression density and stable implosion. The facility-specific laser imprint pattern is considered in the optimization, which makes the pulse design more relevant. The designer is applied to the novel double-cone ignition scheme, and simulation shows that the optimized pulse increases the areal density expectation by 16% in one dimension, and the clean-fuel thickness by a factor of four in two dimensions. This pulse shape designer could be a useful tool for direct-drive ICF instability control.

Characterizing exact energy density distributions for laser-accelerated ion bunches in a medium is challenging due to very high beam intensities and the electro-magnetic pulse emitted in the laser–plasma interaction. Ion-bunch energy acoustic tracing allows for reconstructing the spatial energy density from the ionoacoustic wave generated upon impact in water. We have extended this approach to tracing ionoacoustic modulations of broad energy distributions by introducing thin foils in the water reservoir to shape the acoustic waves at distinct points along the depth–dose curve. Here, we present first simulation studies of this new detector and reconstruction approach, which provides an online read-out of the deposited energy with depth within the centimeter range behind the ion source of state-of-the-art laser–plasma-based accelerators.